For the past five years, data analyst software company Domo has kept its thumb on the pulse of internet usage. Their research has revealed some interesting trends and changes that have accompanied the dramatic growth in internet usage.
There’s no doubt people are spending a lot of time on the internet. The things we do on the internet generate data. Clicks, taps, swipes, likes, and shares are all recorded—digital footprints left behind us in the electronic ether. The canny and savvy are collecting that data, studying it, and using it to make decisions. Starting back in 2013, Domo began releasing yearly “Data Never Sleeps” infographics: snapshots of data being generated every minute on the internet that illustrate just how useful this data can be.
Comparing the data from these infographics year-to-year reveals the shocking amount of growth the internet is experiencing, and where people are spending their time online. Let’s take a look at some of the information, and how it’s changed over the years.
Back in 2000, there were only 400 million people online. While that may sound like a lot at first, it’s only a fraction of the world’s population. More recent years have seen populations a full order of magnitude larger. 2012, when Domo first started putting this data together, saw an online population of 2.5 billion. That’s almost the combined population of India and China (which, for the record, is a lot of people). It didn’t stop there, though. In 2017, that number rose to 3.7 billion, which is more than half the number of humans on the planet, and that’s not even adjusting for the population of babies and technophobic older people.
Social media has been rapidly expanding in recent years, with platforms quickly ballooning with rising numbers of users and increased usage. Facebook, that cornerstone of electronic social infrastructure, was only sharing 684,478 pieces of content a minute back in 2013. The very next year, that number shot up to 2,460,000. At least half of those were over-politicized nonsense.
Twitter, which didn’t appear on the first edition of 'Data Never Sleeps,' has likewise been building steadily. In 2014, Twitter users were tweeting at a rate of 277,000 a minute. The next year, it was 347,222, and by 2017 it was 456,000. Even with Twitter’s growth, though, Snapchat has overtaken it. 2015 saw 284,722 photos shared a minute, but that number nearly doubled in two years to 527,760. That just goes to show that a picture’s worth at least 140 characters.
Meanwhile, Instagram has seen some strange ups and downs. In 2013, users were posting 3,600 new photos a minute. The very next year, that number exploded to 216,000 (an increase of 6000%). By 2017, though, it had calmed back down to a more reasonable 46,740 a minute. Why the sudden spike and drop? Maybe we finally realized that there’s only so many ways we can photograph a latte.
Google is another data source that’s been on the rise. In 2013, they were receiving over 2,000,000 search queries, a figure that had doubled by the following year. By 2017, however, the number had dipped slightly to just 3,607,080 searches a minute, just to prove that nobody’s popular 100% of the time.
Let’s face it—between Youtube cat videos and binge watching Friends on Netflix, people are spending a lot of time streaming online, though apparently less this year than average. Netflix users were streaming 77,160 hours of video a minute in 2015, and 86,805 hours a minute in 2016, but this year the number dropped to 69,444. We’re hoping it had nothing to do with the removal of The Fast and the Furious.
What’s really interesting is not how much is being watched on Youtube, but how much is being added. 2013 was only seeing 48 hours of new video added each minute. In 2014 it was 72 hours a minute, followed by a jump to 300 hours a minute in 2015, and 400 a minute in 2016. We’re not entirely sure who’s watching all this content, but it’s definitely out there.
Like we said, there’s a lot to learn from the data as it fluctuates and grows. Collecting, organizing, and getting the most from data like this, however, will likely take the help of data analysis software. That is, unless, you want to crunch all those numbers and plot all those graphs yourself.